سی حرفی ۔۶
الف
الٰہی بھیج ماہی نوں تھکے نین وچاری دے
لگی سانگ سینے وچ ڈاہڈی، کیتے قول اقراری دے
برہوں بن رسولی پنگرے، جاگے پھٹ بیماری دے
آکھ حنیف نہ ملیا ماہی، ٹُٹے جوش خماری دے
ب
برباد کیتا چا نیناں ، لگے وانگ کٹاری دے
نیوں لگا چخہ چڑھ بہنا، رونے عمراں ساری دے
نین نشیلے کردے حیلے، چھوپے پا دل داری دے
آکھ حنیف نہ ملیا ماہی، لکھے لیکھ لکھاری دے
ت
توے تے روٹی سڑدی جیوں کر ہِکے پاسے تے
دل جگر تے چکی چلے ، غلہ جیویں خراسے تے
عاشق نال رقیب سڑیندے جیویں معشوق دے ہاسے تے
آکھ حنیف نہ ملیا ماہی، جیوندے رہے دلاسے تے
ث
ثمر جے پیار دا چاہویں، عاجز پکڑ حلیمی نوں
گھر آئے دی عزت کرنی ہو کے کھڑا تعظیمی نوں
ونڈیں پیار جگت وچ بہتا، بھلیں نہیں کریمی نوں
آکھ حنیف نہ ملیا ماہی، سِک دے یار قدیمی نوں
ج
جوانی ایویں گزری، کدی نہ سدیا یاراں نے
رُٹھے یار ، غماں رُت آئی، موڑے منہ بہاراں نے
وچ حیرانی، سرگردانی، فانی ہوئے ہزاراں نے
آکھ حنیف نہ ملیا ماہی، ہو گئے حال بیماراں نے
ح
حاصل کی محبت اندر، سر بدنامیاں چائیاں نی
نعمت کھانے ، صاف پوشاکاں، مڈھوں منوں بھلائیاں نی
چنتے ، فکر، اندیشے آئے ، کر دے غم، چڑھائیاں نی
آکھ حنیف نہ ملیا ماہی، کیتیاں بے وفائیاں نی
خ
خدا دی ذات نرالی ویکھے ایس بیماری نوں
عشق ازل دا روگ اولا، کھاندا برہوں ماری نوں
وچ جدائی رہی ترہائی، وصل نہ درداں ماری نوں
آکھ حنیف نہ ملیا ماہی، بخشیں اوگنہاری نوں
د
دوائی روگ میرے دی، باہجھوں نہیں سجن دے کو
دے دیدار مرے دل دارا، موتی آس دے...
Ashaykh Mahmūd bin Abī Bakr bin Abīulala bin Alī Al-bukhārī Al-kalābādhī is one of scholars of Mirāth. He was born in 644 A.H. And died in 700 A.H. He was a man of eminence in Central Asia. He visited many metropolitan cities across the world to get knowledge. During his foreign visits, he contacted great scholars of Islamic sciences. Similarly, thousands of students used to attend his lectures. Allāmah Kalābādhī was a man of letters. He wrote many books. Famous of them are: Ḥall ul Frāi Fī Sharah Naẓm Assirājiyah, Ḍaw us Sirāj Fī Sharah Assirājiyah, Mushtabeh un Nasab Fī Asmā ur Rijāl, Mujamush Shuyūkh, Al Minhāj Al Muntakhab.
Adaptive Soft Computing Synergistic Paradigms for VSC Based FACTS Damping Controls Since their inception, damping of Low Frequency Oscillations (LFOs) has been a critical issue in electric power systems. Voltage Source Converter (VSC) based Flexible AC Transmission Systems (FACTS) have a renowned capability for rapid regulation of various network quantities, thus being a serious candidate for future power system control and smart grids. VSC based FACTS have built in capability of absorbing or delivering reactive power. FACTS controllers when equipped with efficient supplementary damping control combat LFOs. Although, a large research investment in efficient damping control for FACTS and advancement in the field of Artificial Intelligence (AI) has led to more robust controls. Even then, there is a growing realization that the contribution to damping performance enhancement should be more rigorously addressed for different tradeoffs, such as complexity and control effort smoothness. This dissertation puts forth the claim that efficient damping control strategy to improve application quality in terms of damping performance, control effort smoothness and execution time is essential for a high performance FACTS supplementary control. This work is a design paradigm shift from conventional Takagi Sugeno Kang (TSK) based control to advanced control based on hybrid Soft Computing (SC) techniques. SC techniques are the most lucrative choice to supplementary damping control design for their optimal performance delivery in critical applications with low complexity and high precision. The direct focus of this research is to exploit the potential of hybrid SC paradigms, obtained from diversified domains such as signal processing (Fourier and wavelets), applied mathematics (Bsplines and polynomials) and AI (neural and fuzzy), to name a few. A modular approach for optimization of overall Multiple Input Single Output (MISO) TSK structure to speculate optimal combination of antecedent and consequent parts has been proposed. The contributions of this framework are the ixdamping performance improvement with smooth control effort and improved convergence speed. The work, proposed in this thesis, has further been extended to Multiple Input Multiple Output (MIMO) structure. The parameters of controller are updated online, using gradient descent based backpropagation algorithm, to avoid offline training overhead. These synergistic paradigms are later used with indirect Multiple Input Single Output (MISO) and MIMO control to ruminate optimal control schemes. The convergence analysis based on Lyapunov stability criteria has been used to ensure the stability of control scheme and to derive an upper bound on the learning rates. In case of MIMO control, convergence is guaranteed using Adaptive Learning Rates (ALRs). These schemes are applied successively to Single Machine Infinite Bus System (SMIB) with single FACTS, multimachine system with single FACTS and multimachine system with multitype FACTS controllers. The proposed control schemes have been tested for different contingencies and various operating conditions. Finally, the qualitative behavior of all the control paradigms has been quantified using different performance indices that support the nonlinear time domain simulation results. The statistics also support the claim that an ideal performance of a supplementary damping control demands a perfect match between antecedent and consequent part of the NeuroFuzzy network. The frequency domain analysis using Wigner-Ville Distribution (WVD) has also been carried out to analyze the frequency spectra of control effort for smoothness validation. The proposed hybrid control paradigms give better performance in transient and steady-state regions.