串联输水明渠PID多指标自适应算法及仿真研究
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摘要
经典PID控制的控制器参数经整定后一般设为定值,当控制对象参数受环境影响而发生改变时,其控制性能会有所降低。针对大型输水明渠这一特殊的控制系统,为适应受控对象的状态变化,保持较好的控制效果,提出一种可在线调节控制器参数的自适应PID控制算法,并针对多种优化目标进行分析、比选。该算法采用绝对值误差积分IAE与衰减率DAM、超调量OVR作为性能指标参数,通过控制器参数与性能指标的函数关系,提出自适应规则,根据该规则在线调节PID控制器的主要参数Kp、Ki值,使系统动态响应及控制性能进入优化区域。通过对某大型调水工程输水渠道系统干渠串联渠系进行建模仿真,结果表明经过自适应调整,渠系在常规PID算法的基础上系统闸门超调量降低9%～21%、闸门调节次数至少减少1～2次,稳定时间提前15小时以上。可见自适应优化算法对于变化的控制对象,能根据选定的性能指标进行控制器参数的自我优化,不依赖精确的数学模型,尤其针对受控对象部分参数存在缓慢时变的特点有针对性的优化,对于我国广大灌区渠系运行调度以及大型输配水工程的运行管理具有一定的参考价值和应用前景。
The controller parameters of the classic PID control are generally set as fixed values after being tuned. When the parameters of the control object are changed by the environment,the control performance will be reduced. Targeted at the special control system of large-scale open channel,and to adapt to the state change of the controlled object and maintain better control effect,this paper proposes an adaptive PID control algorithm that can adjust controller parameters on-line and analyzes and compares various optimization goals. The algorithm uses Integral of Absolute Magnitude of Error( IAE) and Damping Rate( DAM),Overshoot( OVR) as the performance parameters. According to the functional relationship between controller parameters and performance indexes,adaptive rules are proposed. According to the adaptive rules,the main parameters Kpand Kiof PID controller are adjusted online until the system dynamic response and control performance enter the optimization area. Through the modeling and simulation of the tandem pool on the main channel of the water conveyance channel system of a large-scale water diversion project,the results show that after adaptive adjustment,the system can reduce the overshoot of the gate by 9%～ 21% on the basis of the conventional PID algorithm. The number of gate adjustments is reduced by at least 1 or 2 times,and the stabilization time is advanced by more than 15 hours. It can be seen that the adaptive optimization algorithm can self-optimize the controller parameters according to the selected performance index for the changing control object,and doesn't depend on the exact mathematical model,especially for the controlled object's partial parameters have slow time-varying characteristics. The algorithm has certain reference value and application prospects for the operation and management of the canal system of large-scale irrigation districts and large-scale transmission and distribution projects in China.
The controller parameters of the classic PID control are generally set as fixed values after being tuned. When the parameters of the control object are changed by the environment,the control performance will be reduced. Targeted at the special control system of large-scale open channel,and to adapt to the state change of the controlled object and maintain better control effect,this paper proposes an adaptive PID control algorithm that can adjust controller parameters on-line and analyzes and compares various optimization goals. The algorithm uses Integral of Absolute Magnitude of Error( IAE) and Damping Rate( DAM),Overshoot( OVR) as the performance parameters. According to the functional relationship between controller parameters and performance indexes,adaptive rules are proposed. According to the adaptive rules,the main parameters Kpand Kiof PID controller are adjusted online until the system dynamic response and control performance enter the optimization area. Through the modeling and simulation of the tandem pool on the main channel of the water conveyance channel system of a large-scale water diversion project,the results show that after adaptive adjustment,the system can reduce the overshoot of the gate by 9%～ 21% on the basis of the conventional PID algorithm. The number of gate adjustments is reduced by at least 1 or 2 times,and the stabilization time is advanced by more than 15 hours. It can be seen that the adaptive optimization algorithm can self-optimize the controller parameters according to the selected performance index for the changing control object,and doesn't depend on the exact mathematical model,especially for the controlled object's partial parameters have slow time-varying characteristics. The algorithm has certain reference value and application prospects for the operation and management of the canal system of large-scale irrigation districts and large-scale transmission and distribution projects in China.
引文
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[16]崔巍,陈文学,穆祥鹏.长距离明渠调水工程蓄量动态调节控制算法研究[J].中国水利水电科学研究院学报,2015,13(6):421-427.
[17]吴辉明,雷晓辉,秦韬,等.南水北调中线渠系蓄量补偿运行控制方式[J].南水北调与水利科技,2015,(4):788-792.
[18]曹玉升,畅建霞,黄强,等.南水北调中线输水调度实时控制策略[J].水科学进展,2017,28(1):133-139.
[19] J K.自适应控制理论及应用[M].西安:西北工业大学出版社,2005:9-13.
[20] Gupta P,Guenther K,Hodgkinson J,et al. Performance Monitoring and Assessment of Neuro-Adaptive Controllers for Aerospace Applications Using a Bayesian Approach[C]∥AIAA Guidance,Navigation,and Control Conference and Exhibit,2005.
[21]廖健,何琳,徐荣武.无阀电液伺服操舵装置的单神经元自适应PID控制研究[J].海军工程大学学报,2015,27(6):93-98.
[22] Clemmens A J,Kacerek T F,Grawitz B,et al. Test cases for canal control algorithms[J]. Journal of Irrigation&Drainage Engineering,1998,124(1):23-30.
[23]武汉大学.输水渠道系统运行仿真与控制软件V1.0[P].中国:2011SR034392,2011-06-03.
[2] Clemmens A J. Water-Level Difference Controller for Main Canals[J]. Journal of Irrigation&Drainage Engineering,2012,138(1):1-8.
[3] Wahlin B T. Performance of Model Predictive Control on ASCE Test Canal 1[J]. Journal of Irrigation and Drainage Engineering,2004,130(3):227-238.
[4] Hashemy S M,Monem M J,Maestre J M,et al. Application of an In-Line Storage Strategy to Improve the Operational Performance of Main Irrigation Canals Using Model Predictive Control[J]. Journal of Irrigation and Drainage Engineering,2013,139(8):635-644.
[5]王长德,张礼卫.下游常水位水力自动控制渠道运行动态过程及数学模型的研究[J].水利学报,1997,(11):11-19.
[6]王长德,柳树票,崔玉炎,等.多渠段串联渠系P+PR控制[J].武汉大学学报(工学版),2002,35(1):15-19.
[7]范杰,王长德,崔巍,等.渠道运行系统中的模糊PID联合控制研究[J].灌溉排水学报,2003,22(4):59-62.
[8]管光华,王长德,范杰,等.鲁棒控制在多渠段自动控制的应用[J].水利学报,2005,36(11):1 379-1 384.
[9]姚雄,王长德,李长菁.分层模糊控制器在渠道运行系统中的应用[C]∥全国灌区及水工建筑物防渗抗冻胀与水量监控学术研讨会,2005.
[10]韩延成,高学平,涂向阳,等.基于CMAC神经网络的自适应渠道输水自动控制研究[J].灌溉排水学报,2007,26(2):76-79.
[11]韩延成,高学平.基于RBF人工神经网络的下游常水位自适应渠道输水控制研究[J].西北农林科技大学学报:自然科学版,2007,35(8):202-206.
[12]管光华,王长德,冯晓波.大型渠系联合运行状态空间模型不确定性的描述与度量[J].水科学进展,2008,19(2):251-256.
[13]管光华,王长德.长渠系稳态恒定流解法与非恒定流解法差异及对控制方式的影响[J].南水北调与水利科技,2008,6(5):13-17.
[14] Guan G,Clemmens A J,Kacerek T F,et al. Applying Water-Level Difference Control to Central Arizona Project[J]. Journal of Irrigation&Drainage Engineering,2011,137(12):747-753.
[15]刘国强,闫弈博,王长德,等.长距离渠系冰期运行过渡模式研究[J].武汉大学学报(工学版),2012,45(1):34-40.
[16]崔巍,陈文学,穆祥鹏.长距离明渠调水工程蓄量动态调节控制算法研究[J].中国水利水电科学研究院学报,2015,13(6):421-427.
[17]吴辉明,雷晓辉,秦韬,等.南水北调中线渠系蓄量补偿运行控制方式[J].南水北调与水利科技,2015,(4):788-792.
[18]曹玉升,畅建霞,黄强,等.南水北调中线输水调度实时控制策略[J].水科学进展,2017,28(1):133-139.
[19] J K.自适应控制理论及应用[M].西安:西北工业大学出版社,2005:9-13.
[20] Gupta P,Guenther K,Hodgkinson J,et al. Performance Monitoring and Assessment of Neuro-Adaptive Controllers for Aerospace Applications Using a Bayesian Approach[C]∥AIAA Guidance,Navigation,and Control Conference and Exhibit,2005.
[21]廖健,何琳,徐荣武.无阀电液伺服操舵装置的单神经元自适应PID控制研究[J].海军工程大学学报,2015,27(6):93-98.
[22] Clemmens A J,Kacerek T F,Grawitz B,et al. Test cases for canal control algorithms[J]. Journal of Irrigation&Drainage Engineering,1998,124(1):23-30.
[23]武汉大学.输水渠道系统运行仿真与控制软件V1.0[P].中国:2011SR034392,2011-06-03.
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